CN102932641B - A kind of constant-quality bit rate control method - Google Patents

A kind of constant-quality bit rate control method Download PDF

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CN102932641B
CN102932641B CN201210454382.6A CN201210454382A CN102932641B CN 102932641 B CN102932641 B CN 102932641B CN 201210454382 A CN201210454382 A CN 201210454382A CN 102932641 B CN102932641 B CN 102932641B
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马思伟
司俊俊
王诗淇
高文
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Peking University
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Abstract

The invention provides a kind of constant-quality bit rate control method, relate to technical field of video coding.This algorithm comprises the following steps: first utilize R-Q model to obtain current quantisation parameter; Again by quality-smoothing constrained procedure, by retraining the fluctuation range of PSNR, adjust current quantisation parameter adaptively.The present invention, while guarantee coding efficiency, effectively reduces PSNR fluctuation and the bit rate output fluctuation of encoded video, obtains video encoding quality comparatively stably, reach the object of constant-quality Rate Control.

Description

A kind of constant-quality bit rate control method
Technical field
The present invention relates to technical field of video coding, particularly relate to a kind of constant-quality bit rate control method.
Background technology
Rate Control is the important component part of Video coding, leaves Rate Control, and the application of any video encoding standard all can be restricted.If do not have Rate Control, in the transmitting procedure under band-limited constraint, client buffer district is easy to overflow or underflow occur, thus causes loss of data.The video encoding standard of main flow has himself rate control algorithm applicable in the world, as VM5, the TMN8 etc. H.263 of TM5, MPEG-4 of MPEG-2.
Relation between image fault D and code check R is referred to as rate distortion theory.Relation between R, D can be portrayed with monotonous curve convex under.
Average is zero, and variance is σ 2memoryless Gaussian Profile information source, its probability density function is:
If using mean square error (MeanSquareError, MSE) as the standard weighing distortion, then its rate distortion function is:
or D (R)>=2 -2Rσ 2(2)
In transition coding, dct transform coefficient uses laplacian distribution p (x)=0.5* Δ * e usually -Δ | × |simulate.For laplacian distribution, its rate distortion function is expressed as:
Wherein, Q is quantization step.Visible when quantization step Q increases distortion D close to information source variance
Rate Control and rate-distortion optimization closely related.Rate Control scheme normally designs based on rate-distortion model.Linear R-Q model as TM5: secondary model R=A (the K σ of R=X/QP, TMN8 2/ QP 2+ C), and the secondary model R=a × MAD/QP+b × MAD of MPEG-4 2/ QP 2.Compare linear R-Q model, the control result of secondary model is more accurate, but computation complexity is very high.Therefore, often kind of rate control algorithm has respective pluses and minuses and range of application.Two key factors affecting rate control algorithm are: level and smooth picture quality and level and smooth buffer state.Y-PSNR (PeakSignalNoiseRatio, the PSNR) curve that level and smooth picture quality shows as video sequence is level and smooth as far as possible, fluctuate little (Δ PSNR is little).The code check (R) of level and smooth buffer state and encoder exports steady as far as possible, code check fluctuation less (Δ R is little).
The mathematic(al) representation of PSNR is:
Wherein, MSE (MeanSquareError) is the mean square deviation between original image and decoded picture pixel, and n is presentation video pixel value figure place used.Obviously, MSE causes owing to quantizing, encoding, and namely MSE is relevant with quantization parameter (QuantizationParameter, QP).The bit rate output of encoder is that the quantification before coding must affect bit rate output because produce the actual coding of frame of video.So bit rate output is also relevant to QP.
From the above, quantization parameter QP affects PSNR and the bit rate output of encoded video simultaneously.So the fluctuation of video sequence QP must cause the fluctuation of PSNR and bit rate output.Therefore, obtain that level and smooth picture quality and level and smooth code check export will the fluctuation of control QP, makes it little as far as possible, reaches stable state.
So it is two standards weighing rate control algorithm quality that level and smooth picture quality and level and smooth code check export, and the sharpening result of these two key factors needs to be reached by the smoothness of adjustment quantization parameter QP.
VM5 and the ρ territory rate control algorithm of the TM5 of MPEG-2, TMN8, MPEG-4 is H.263 all based on inter-frame complexity and rate-distortion model.Because frame complexity difference each in video sequence may be very large, this will cause QP to change greatly frame by frame, thus causes PSNR and bit rate output to fluctuate larger.And along with the Internet, the particularly development of mobile Internet, smooth, stable video playback demand is growing.Therefore, design constant-quality bit rate control method, effective control coding video quality fluctuation has broad prospect of application.
Summary of the invention
The object of the present invention is to provide a kind of constant-quality bit rate control method, while guarantee coding efficiency, effectively reduce PSNR fluctuation and the bit rate output fluctuation of encoded video, obtain video encoding quality comparatively stably, reach the object of constant-quality Rate Control.
In order to reach above object, the embodiment of the invention discloses a kind of constant-quality bit rate control method, comprising the following steps:
R-Q model is first utilized to obtain current quantisation parameter;
Again by quality-smoothing constrained procedure, by retraining the fluctuation range of PSNR, adjust current quantisation parameter adaptively.
Further, preferred as one, quality-smoothing constrained procedure specifically comprises:
Utilize the picture quality that picture quality method of estimation estimation current quantisation parameter coding present image produces;
According to the picture quality of estimation and the difference of encoded video frame images quality average, adjust quantization parameter further.
Further, preferred as one, according to the picture quality of estimation and the difference of encoded video frame images quality average, adjust quantization parameter further, if the picture quality estimated and encoded video frame images quality average difference are less than pre-set threshold value, then do not adjust; If be greater than pre-set threshold value, then an objective image quality is set, by feedback regulation, calculates a new quantization parameter.
Further, preferred as one, utilize R-Q model decision quantization parameter, the complexity information of some encoded frames before considering present frame, described complexity information is the complexity weighted sum of encoded all frames above.
Further, preferred as one, complexity weighted sum, calculates according to the distance of a two field picture apart from present frame, and distance is nearer, and weighted value is larger.
Further, preferred as one, utilize picture quality method of estimation, use the quantization parameter of present frame and complexity to estimate the PSNR of present frame.
Further, preferred as one, complexity information is obtained by fast motion estimation.
Further, preferred as one, be applied with quantization parameter self-adaptative adjustment in GOP level, according to the target bit of previous GOP and the initial quantization parameters of the current GOP of discrepancy adjustment of generation bit number.
Further, preferred as one, be applied with the regulation and control of quantization parameter self adaptation in frame level, according to the target bit of encoded frame of video and the quantization parameter of the discrepancy adjustment present frame of generation bit number.
Further, preferred as one, be applied with the regulation and control of quantization parameter self adaptation in macro-block level, when a coding macro block, according to the quantization parameter of current macro complexity adjustment current macro.
The present invention is owing to adopting linear R-Q model and new PSNR model, and based on the quality-smoothing bounding algorithm of this model, while guarantee coding efficiency, effectively reduce PSNR fluctuation and the bit rate output fluctuation of encoded video, obtain video encoding quality comparatively stably, reach the object of constant-quality Rate Control.
Accompanying drawing explanation
When considered in conjunction with the accompanying drawings, by referring to detailed description below, more completely can understand the present invention better and easily learn wherein many adjoint advantages, but accompanying drawing described herein is used to provide a further understanding of the present invention, form a part of the present invention, schematic description and description of the present invention, for explaining the present invention, does not form inappropriate limitation of the present invention, wherein:
Fig. 1 PSNR model, shows the relation of PSNR and the QP-log (SATD) of QCIF format video sequence;
Fig. 2 constant-quality bit rate control method flow chart;
The flatness comparison diagram of Fig. 3 CIF form football sequence under the present invention and AVSRM0.9 rate control algorithm;
The bit rate output fluctuation situation map of Fig. 4 QCIF form foreman sequence under the present invention and AVSRM0.9 rate control algorithm;
The R-Q Performance comparision figure of Fig. 5 QCIF form football sequence under the present invention and AVSRM0.9 rate control algorithm;
Embodiment
For enabling above-mentioned purpose, feature and advantage become apparent more, and below in conjunction with the drawings and specific embodiments, the present invention is further detailed explanation.
The embodiment of the present invention devises a kind of constant-quality bit rate control method, while reduction computation complexity, the bit rate output of encoded video and Y-PSNR can be made comparatively level and smooth, effectively reduce quality fluctuation.This rate control algorithm mainly comprises two parts: one is the adaptive rate control algorithm based on linear R-Q model, and two is the quality-smoothing bounding algorithms based on PSNR restricted model.
The embodiment of the present invention proposes a kind of linear R-Q model, as shown in formula (4):
Wherein:
N is current video frame number to be encoded;
Qcom is the constant between 0 ~ 1, usually gets 0.6;
QP nit is the quantization parameter of the n-th two field picture;
T nit is the target bit of the n-th two field picture;
R nit is the actual coding bit number of the n-th two field picture;
α is model parameter;
be the SATD weighted sum of all encoded n two field pictures, SATD is SumofAbsoluteTransformedDifference (definitely conversion difference sum).W ibe defined as follows shown in formula:
The present invention, according to VBV (VideoBufferVerifier) buffer fullness, is current frame of video distribution code check to be encoded.Shown in (6), if target bit rate is R, encoded video sequence frame per second is Fr, then the target bit of current frame of video to be encoded is T
T＝R/Fr-Δ(6)
Wherein, Δ reflects the adjustment that the state contraposition of current vbv buffer distributes, and its computing formula is such as formula shown in (7), and W represents the difference of current vbv buffer degree of filling and initial vbv buffer degree of filling, and Z is constant, and in experiment, value is 0.1.
The embodiment of the present invention devises the quantization parameter self adaptation regulating strategy of GOP level, frame level, macro-block level, under the condition not increasing computation complexity, effectively improves rate control accuracy.First, be the quantization parameter self adaptation regulating strategy of a GOP level.Code check according to previous GOP overflows situation, the initial Q P of the current GOP of adaptive setting.Secondly, be frame level QP self adaptation regulating strategy.According to current code check Expenditure Levels, the QP of self-adaptative adjustment present frame, code check is overflowed can be regulated timely.Finally, be the QP self-adaptative adjustment of macro-block level.According to current macro complexity information, its QP of self-adaptative adjustment, makes the coding of current macro more reasonable, effectively utilizes code check.
The embodiment of the present invention proposes a kind of new PSNR model.Experimentally result, has good linear relationship between PSNR and (QP-log (SATD)), as shown in Figure 1.Therefore can obtain such as formula the PSNR model shown in (8).PSNR model compared to classics: PSNR=α × QP+ β, the new model that the present invention proposes considers image complexity information, can better react the quantization parameter of different images and the relation of PSNR.
PSNR＝α×(QP-logSATD)+β(8)
The embodiment of the present invention devises a kind of algorithm carrying out constant-quality Rate Control according to above-mentioned distortion model.Before coding, a fast motion estimation is done to image, obtain the SATD information of image.In conjunction with the quantization parameter QP that rate control algorithm obtains, can by the Y-PSNR PSNR of formula (8) estimated image.If the average peak signal to noise ratio of encoded some two field pictures is PSNR_avg, by retraining the fluctuation range of PSNR, adjust QP adaptively.Restriction relation is | PSNR-PSNR_avg| < ε.Such as, current quantization parameter of trying to achieve is QP 0, corresponding Y-PSNR PSNR can be estimated by formula (8) 0.If PSNR 0exceed the PSNR fluctuation range of setting, then self-adaptative adjustment QP makes PSNR fluctuate within constraint.Meet code check, the two QP value retrained of quality fluctuation participates in coding as final quantization parameter.
So, control code check fluctuation adaptively, comparatively level and smooth coding quality can be obtained.
To sum up, the code check of the constant-quality bit rate control method that proposes of the embodiment of the present invention, PSNR double constraints model are such as formula shown in (9):
Embodiment:
First, for encoding code stream arranges a vbv buffer, during a coding frame of video, carry out position distribution according to current buffer degree of filling.Secondly, the linear R-Q model (formula (4)) utilizing us to propose and designed a series of quantization parameter self adaptation regulating strategies, calculate the quantization parameter QP of a frame level.Again, the PSNR model (formula (8)) utilizing the present invention to propose, detect current QP whether can meet PSNR fluctuation be no more than preset range.If exceeded, then correspondingly adjust QP, make the double constraints of its As soon as possible Promising Policy code check, PSNR, and participate in actual quantization and the coding of frame of video as final quantization parameter.Finally, when a coding macro block, according to the complexity information of current macro, suitably adjustment frame level QP, obtains the quantization parameter of encoding current macroblock, effectively to utilize code check, obtains good coding quality.Below, on AVSRM, be embodied as example with this invention, introduce its execution mode in detail, see Fig. 2.
The first step: S1, initialization vbv buffer.If buffer size is M, initial buffer fullness is B 0=M*0.9, if B represents current buffer degree of filling, S2, reads in a frame;
Second step: S3, position are distributed.If present frame target bit is T, then its computing formula is such as formula shown in (10), and wherein R represents target bit rate, and Fr represents frame per second.
T＝R/Fr-Δ(10)
Wherein, Δ computational methods are such as formula shown in (11), and W represents the difference of current buffer degree of filling and initial buffer fullness, and Z is constant, and in experiment, value is 0.1:
3rd step: S4, S5, image complexity are estimated.Do a fast motion estimation to present frame, calculate its SATD (SumofAbsoluteDifference), the complexity as present frame is estimated.
4th step: S6, quantization parameter decision-making.If present frame is I/P frame, then the linear R-Q model of the present invention's proposition, namely formula (4) calculates the quantization parameter QP of present frame.If present frame is B frame, then its quantization parameter is obtained by the QP interpolation of adjacent I/P frame.Computing formula such as formula shown in (12), wherein QP 1and QP 2the quantization parameter value of adjacent I/P frame respectively, d 1with d 2the difference of the frame number of present frame and two reference frames respectively.
5th step: buffer fullness retrains.Check whether the quantization parameter QP that the 3rd step calculates can cause vbv buffer overflow or underflow.
6th step: S7, GOP level QP self adaptation regulates and controls.I frame if current, then according to previous GOP 0the current GOP of coding situation adaptive decision-making 1initial Q P.
if|R prev-T prev|＞ε
thenQP＝(QP avg_prev+QP)/2±Δ(13)
Wherein, R prev, T prevprevious GOP respectively 0generation code check and target bit rate, QP avg_prevgOP 0in the mean value of quantization parameter QP of all coded frame.
7th step: S7, frame level QP self adaptation regulate and control.According to the QP of current code check Expenditure Levels self-adaptative adjustment present frame.The quantization parameter of code check relative to degree of overflowing the up and down adjustment present frame of target bit rate has been consumed according to current.Such as current code check overflows, then present frame QP is at least not less than the QP of last core frames.This strategy only acts on core frames (I/P), and B frame only need ensure that self QP is not less than the QP of its reference frame.Concrete regulate and control method is as follows:
ifoverflow＜αthenQP＝QP-Δ
elseifoverflow＞βthenQP＝QP+Δ
Wherein, generatedBits is the bit number consumed at present, and targetBits is the general objective bit number of encoded frame, and Bitrate is target bit rate, α, β, and Δ is constant, and α < 1, β > 1.
8th step: S8, PSNR are model constrained.The QP obtained by the 9th step can by PSNR model, namely formula (8) calculates the PSNR of an expection, if this PSNR of S9 meets formula (15), then the QP of the 7th step is namely as the final quantization parameter result of decision, for quantification, the coding of present frame.
|PSNR-PSNR_avg|＜ε(15)
Wherein, PSNR_avg is the PSNR mean value of encoded frame above.
S10 otherwise, QP value needs decision-making again.First an initial value is calculated by formula (16), S11 and then perform the QP self adaptation regulating strategy of the 7th step.
QP＝(PSNR_avg±ε-β)/α+logSATD(16)
Wherein, α, β are the model parameters of PSNR and QP linear restriction.Having encoded after a frame uses least square method to upgrade its value.Shown in (13):
9th step: S12, S13, macro-block level QP self adaptation regulate and control.In one two field picture, the complexity possibility difference of different macro block is very large, and namely residual information possibility difference is very large.Account for the weight of whole frame SATD according to the SATD of current MB, the QP value of self-adaptative adjustment current block, Data Rate Distribution can be made more reasonable.Method of adjustment is such as formula shown in (14):
Wherein,
Mb_satd is the SATD value of current macro;
Avg_mb is the average SATD value of present frame for macro block;
QP frameit is frame level quantized parameter;
QP mbit is the current macro quantization parameter treating decision-making;
δ, Δ is constant.
Tenth step: S14, parameter upgrade.Encode after a two field picture, correlation model parameters will have been upgraded according to the coding situation of present frame.And upgrade vbv buffer degree of filling according to formula (19), wherein bits is the actual coding bit number of present frame.S15, QP preserve.
B＝B+R/Fr-bits(19)
According to above step, encode frame by frame, just can realize constant-quality Rate Control.
We test respectively to the coding efficiency of algorithm and flatness thereof, and compare with the result of the former rate control algorithm of Anchor and AVS.
1) flatness:
Compared with AVSRM0.9 rate control algorithm, algorithm in this paper effectively reduces PSNR variance yields, namely has significant coding quality smooth effect, reaches the object of constant-quality Rate Control.
More intuitively, we respectively provide the PSNR curve of cyclical fluctuations and the bit rate output curve of cyclical fluctuations of a sequence in three resolution.As shown in Figure 3, the bit rate output curve of cyclical fluctuations as shown in Figure 4 for the PSNR curve of cyclical fluctuations.Result shows, relative to AVSRM0.9 rate control algorithm, the present invention can obtain comparatively level and smooth PSNR and comparatively stable bit rate output, namely enough obtains the video encoding quality of relative smooth.
2) coding efficiency:
Compared with former AVSRM0.9 rate control algorithm, the present invention qcif cif wvga tri-kinds of video formats cycle tests under, there is suitable coding efficiency.But when low bit-rate, the present invention can obtain R-Q performance more better than the former rate control algorithm of AVSRM.We provide the R-Q curve of an exemplary sequence, as shown in Figure 5.
In sum, the present invention proposes a kind of new R-Q model and PSNR model, and devises based on these two model constrained frame level constant-quality bit rate control methods.This rate control algorithm carries out position distribution based on vbv buffer degree of filling, based on R-Q model and PSNR
The double constraints of model carries out quantization parameter decision-making, and devises the quantization parameter self adaptation regulating strategy of GOP level, frame level, macro-block level, when ensureing Rate Control accuracy and coding efficiency, can obtain the coding quality of comparatively flat bone.Compared with the rate control algorithm of AVSRM0.9, the present invention uses linear R-Q model, and computation complexity is relatively low.Rate control accuracy and coding efficiency loss are all within the scope of acceptable (table 3).And the present invention effectively reduces coding quality fluctuation and bit rate output fluctuation, reaches the object of level and smooth quality control, can obtain better encoding efficiency.
Although the foregoing describe the specific embodiment of the present invention, but those skilled in the art is to be understood that, these embodiments only illustrate, those skilled in the art, when not departing from principle of the present invention and essence, can carry out various omission, replacement and change to the details of said method and system.Such as, merge said method step, thus then belong to scope of the present invention according to the function that the method that essence is identical performs essence identical to realize the identical result of essence.Therefore, scope of the present invention is only defined by the appended claims.

Claims (10)

1. a constant-quality bit rate control method, is characterized in that, comprises the following steps:
First utilize R-Q model to obtain the quantization parameter QP of the two field picture in current video frame number to be encoded, described R-Q model is as follows:
T n = &alpha; &times; ( &Sigma; i = 0 n w i &times; SATD i ) 1 - qcom &times; R n - 1 &times; Q P n - 1 ( &Sigma; i = 0 n - 1 w i &times; SATD i ) 1 - qcom &times; Q P n
Wherein:
N is current video frame number to be encoded;
Qcom is the constant between 0 ~ 1;
QP nit is the quantization parameter of the n-th two field picture;
T nit is the target bit of the n-th two field picture;
R nit is the actual coding bit number of the n-th two field picture;
α is model parameter;
the SATD weighted sum of all encoded n two field pictures, w ibe defined as follows shown in formula:
w i = 0.5 n - i / &Sigma; i = 0 n 0.5 n - i ;
By quality-smoothing constrained procedure, by the fluctuation range of the Y-PSNR PSNR of constraints graph picture, adjust the quantization parameter QP of two field picture adaptively;
PSNR＝α×(QP-logSATD)+β
α is R-Q model parameter, and SATD is the absolute transformed sum of encoded all two field pictures, and β is the parameter of setting;
If the average peak signal to noise ratio of encoded some two field pictures is PSNR_avg, by retraining the fluctuation range of PSNR, adjust the quantization parameter QP of two field picture adaptively, restriction relation is:
|PSNR-PSNR_avg|＜ε
ε is the error parameter of setting.
2. constant-quality bit rate control method according to claim 1, is characterized in that, described quality-smoothing constrained procedure specifically comprises:
Utilize the picture quality that picture quality method of estimation estimation current quantisation parameter coding present image produces;
According to the picture quality of estimation and the difference of encoded video frame images quality average, adjust quantization parameter further.
3. constant-quality bit rate control method according to claim 2, it is characterized in that, described according to the picture quality of estimation and the difference of encoded video frame images quality average, further adjustment quantization parameter, if the picture quality estimated and encoded video frame images quality average difference are less than pre-set threshold value, then do not adjust; If be greater than pre-set threshold value, then an objective image quality is set, by feedback regulation, calculates a new quantization parameter.
4. constant-quality bit rate control method according to claim 1, it is characterized in that: describedly utilize R-Q model decision quantization parameter, the complexity information of some encoded frames before considering present frame, described complexity information is the complexity weighted sum of encoded all frames above.
5. constant-quality bit rate control method according to claim 4, is characterized in that, described complexity weighted sum, calculates according to the distance of a two field picture apart from present frame, and distance is nearer, and weighted value is larger.
6. constant-quality bit rate control method according to claim 1, is characterized in that: describedly utilize picture quality method of estimation, uses the quantization parameter of present frame and complexity to estimate the PSNR of present frame.
7. according to the constant-quality bit rate control method in claim 4 to 6 described in any one, it is characterized in that, described complexity information is obtained by fast motion estimation.
8. constant-quality bit rate control method according to claim 1, is characterized in that, is applied with quantization parameter self-adaptative adjustment in GOP level, according to the target bit of previous GOP and the initial quantization parameters of the current GOP of discrepancy adjustment of generation bit number.
9. constant-quality bit rate control method according to claim 1, is characterized in that, is applied with the regulation and control of quantization parameter self adaptation in frame level, according to the target bit of encoded frame of video and the quantization parameter of the discrepancy adjustment present frame of generation bit number.
10. constant-quality bit rate control method according to claim 1, is characterized in that, is applied with the regulation and control of quantization parameter self adaptation in macro-block level, when a coding macro block, according to the quantization parameter of current macro complexity adjustment current macro.
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